Infection with Epstein-Barr virus (EBV) is highly prevalent worldwide, and it has been associated with infectious mononucleosis and severe diseases including Burkitt lymphoma, Hodgkin lymphoma, nasopharyngeal lymphoma, and lymphoproliferative disorders. Although EBV has been the focus of extensive research, much still remains unknown concerning what makes some individuals more sensitive to infection and to adverse outcomes as a result of infection. Here we use an integrative genomics approach in order to localize genetic factors influencing levels of Epstein Barr virus (EBV) nuclear antigen-1 (EBNA-1) IgG antibodies, as a measure of history of infection with this pathogen, in large Mexican American families. Genome-wide evidence of both significant linkage and association was obtained on chromosome 6 in the human leukocyte antigen (HLA) region and replicated in an independent Mexican American sample of large families (minimum p-value in combined analysis of both datasets is 1.4×10−15 for SNPs rs477515 and rs2516049). Conditional association analyses indicate the presence of at least two separate loci within MHC class II, and along with lymphocyte expression data suggest genes HLA-DRB1 and HLA-DQB1 as the best candidates. The association signals are specific to EBV and are not found with IgG antibodies to 12 other pathogens examined, and therefore do not simply reveal a general HLA effect. We investigated whether SNPs significantly associated with diseases in which EBV is known or suspected to play a role (namely nasopharyngeal lymphoma, Hodgkin lymphoma, systemic lupus erythematosus, and multiple sclerosis) also show evidence of associated with EBNA-1 antibody levels, finding an overlap only for the HLA locus, but none elsewhere in the genome. The significance of this work is that a major locus related to EBV infection has been identified, which may ultimately reveal the underlying mechanisms by which the immune system regulates infection with this pathogen.
Many factors influence individual differences in susceptibility to infectious disease, including genetic factors of the host. Here we use several genome-wide investigative tools (linkage, association, joint linkage and association, and the analysis of gene expression data) to search for host genetic factors influencing Epstein-Barr virus (EBV) infection. EBV is a human herpes virus that infects up to 90% of adults worldwide, infection with which has been associated with severe complications including malignancies and autoimmune disorders. In a sample of >1,300 Mexican American family members, we found significant evidence of association of anti–EBV antibody levels with loci on chromosome 6 in the human leukocyte antigen region, which contains genes related to immune function. The top two independent loci in this region were HLA-DRB1 and HLA-DQB1, both of which are involved in the presentation of foreign antigens to T cells. This finding was specific to EBV and not to 12 other pathogens we examined. We also report an overlap of genetic factors influencing both EBV antibody level and EBV–related cancers and autoimmune disorders. This work demonstrates the presence of EBV susceptibility loci and provides impetus for further investigation to better understand the underlying mechanisms related to differences in disease progression among individuals infected with this pathogen.
Despite overwhelming evidence that major depression is highly heritable, recent studies have localized only a single depression-related locus reaching genome-wide significance and have yet to identify a causal gene. Focusing on family-based studies of quantitative intermediate phenotypes or endophenotypes, in tandem with studies of unrelated individuals using categorical diagnoses, should improve the likelihood of identifying major depression genes. However, there is currently no empirically-derived statistically rigorous method for selecting optimal endophentypes for mental illnesses. Here we describe the Endophenotype Ranking Value (ERV), a new objective index of the genetic utility of endophenotypes for any heritable illness.
Applying ERV analysis to a high-dimensional set of over 11,000 traits drawn from behavioral/neurocognitive, neuroanatomic, and transcriptomic phenotypic domains, we identified a set of objective endophenotypes for recurrent major depression in a sample of Mexican American individiauls (n=1122) from large randomly-selected extended pedigrees.
Top-ranked endophenotypes included the Beck Depression Inventory, bilateral ventral diencephalon volume and expression levels of the RNF123 transcript. To illustrate the utility of endophentypes in this context, each of these traits were utlized along with disease status in bivariate linkage analysis. A genome-wide significant quantitative trait locus was localized on chromsome 4p15 (LOD=3.5) exhibiting pleiotropic effects on both the endophenotype (lymphocyte-derived expression levels of the RNF123 gene) and disease risk.
The wider use of quantitative endophentpyes, combined with unbiased methods for selecting among these measures, should spur new insights into the biological mechanisms that influence mental illnesses like major depression.
major depression; recurrent major depression; endophenotype; endophenotype ranking; linkage; family studies
nuclear factor kappa B; gene expression network; principal components factor analysis; linkage analysis; systems genetics
We sought to identify cognitive phenotypes for family/genetic studies of successful cognitive aging (SCA; maintaining intact cognitive functioning while living to late old age).We administered a battery of neuropsychological tests to nondemented nonagenarians (n = 65; mean age = 93.4±3.0) and their offspring (n = 188; mean age = 66.4±5.0) from the Central Valley of Costa Rica. After covarying for age, gender, and years of education, as necessary, heritability was calculated for cognitive functions at three pre-defined levels of complexity: specific neuropsychological functions (e.g., delayed recall, sequencing), three higher level cognitive domains (memory, executive functions, attention), and an overall neuropsychological summary. The highest heritability was for delayed recall (h2 = 0.74, se = 0.14, p < 0.0001) but significant heritabilities involving memory were also observed for immediate recall (h2 = 0.50), memory as a cognitive domain (h2 = 0.53), and the overall neuropsychological summary (h2 = 0.42). Heritabilities for sequencing (h2 = 0.42), fluency (h2 = 0.39), abstraction (h2 = 0.36), and the executive functions cognitive domain (h2 = 0.35) were also significant. In contrast, the attention domain and memory recognition were not significantly heritable in these families. Among the heritable specific cognitive functions, a strong pleiotropic effect (i.e., evidence that these may be influenced by the same gene or set of genes) for delayed and immediate recall was identified (bivariate statistic = 0.934, p < 0.0001) and more modest but significant effects were found for four additional bivariate relationships. The results support the heritability of good cognitive function in old age and the utilization of several levels of phenotypes, and they suggest that several measures involving memory may be especially useful for family/genetic studies of SCA.
Family studies; hispanic population; neuropsychological phenotype; oldest-old; successful cognitive aging
A recent study in a sample of Plains Indians showed association between eight SNPs located in the SGIP1 gene and resting theta electroencephalogram (EEG) power (Hodgkinson et al., 2010). This association appeared to generalize to alcohol use disorders, for which EEG power is a potential endophenotype.
We analyzed a large, diverse sample for replication of the association of these implicated SGIP1 SNPs (genotyped on the Illumina 1M platform) with alcohol dependence (N = 3988) and theta EEG power (N = 1066).
We found no evidence of association of the previously implicated SGIP1 SNPs with either alcohol dependence or theta EEG power (all p > 0.15) in the current sample.
The previously implicated SNPs located in SGIP1 showed no association with alcohol dependence or theta EEG power in the present sample of individuals with European and/or African ancestry. This failure to replicate may be the result of differences in ancestry between the current and original samples.
alcoholism; electroencephalogram; candidate gene association study
Altered mitochondrial DNA (mtDNA) levels have been associated with common diseases in humans. We investigated the genetic mechanism that controls mtDNA levels using genome-wide linkage analyses in families from the Genetic Analysis of Idiopathic Thrombophilia Project (GAIT). We measure mtDNA levels by quantitative real-time PCR in 386 subjects from 21 extended Spanish families. A variance component linkage method using 485 microsatellites was conducted to evaluate linkage and to detect quantitative trait loci (QTLs) involved in the control of mtDNA levels. The heritalibility of mtDNA levels was 0.33 (p = 1.82e-05). We identified a QTL on Chromosome 2 (LOD = 2.21) using all of the subjects, independently on their sex. When females and males were analysed separately, three QTLs were identified. Females showed the same QTL on Chromosome 2 (LOD = 3.09), indicating that the QTL identified in the analysis using all of the subjects was a strong female QTL, and another one on Chromosome 3 (LOD = 2.67), whereas in males a QTL was identified on Chromosome 1 (LOD = 2.81). These QTLs were fine-mapped to find associations with mtDNA levels. The most significant SNP association was for the rs10888838 on Chromosome 1 in males. This SNP mapped to the gene MRPL37, involved in mitochondrial protein translation. The rs2140855 on Chromosome 2 showed association in the analysis using all of the subjects. It was near the gene CMPK2, which encodes a mitochondrial enzyme of the salvage pathway of deoxyribonucleotide synthesis. Our results provide evidence of a sex-specific genetic mechanism for the control of mtDNA levels and provide a framework to identify new genes that influence mtDNA levels.
Although genetic influences on bipolar disorder are well established, localization of genes that predispose to the illness has proven difficult. Given that genes predisposing to bipolar disorder may be transmitted without expression of the categorical clinical phenotype, one strategy for identifying risk genes is the use of quantitative endophenotypes.
The goal of the current study is to adjudicate neurocognitive endophenotypes for bipolar disorder.
Design, Setting, and Participants
709 Latino individuals from the central valley of Costa Rica, Mexico City, Mexico, or San Antonio, Texas participated in the study. 660 of these persons were members of extended pedigrees with at least two siblings diagnosed with bipolar disorder (n=230). The remaining subjects were community controls drawn from each site and without personal or family history of bipolar disorder or schizophrenia. All subjects received psychodiagnostic interviews and comprehensive neurocognitive evaluations. Neurocognitive measures found to be heritable were entered into analyses designed to determine which tests are impaired in affected individuals, sensitive to genetic liability for the illness and genetically correlated with affection status.
Main Outcome Measures
The main outcome measure was neurocognitive test performance.
Two of the 21 neurocognitive variables were not significantly heritable and were excluded from subsequent analyses. Patients with bipolar disorder were impaired on 6 of these cognitive measures compared to non-related healthy subjects. Non-bipolar first-degree relatives were impaired on five of these and three tests were genetically correlated with affection status: digit symbol coding, object delayed response, and immediate facial memory.
This large-scale extended pedigree study of cognitive functioning in bipolar disorder identified measures of processing speed, working memory and declarative (facial) memory as candidate endophenotypes for bipolar disorder.
bipolar disorder; endophenotype; genetics; family studies; neurocognitive; neuropsychological
Copy number variations (CNVs) are a major source of alterations among individuals and are a potential risk factor in many diseases. Numerous diseases have been linked to deletions and duplications of these chromosomal segments. Data from genome-wide association studies and other microarrays may be used to identify CNVs by several different computer programs, but the reliability of the results has been questioned.
To help researchers reduce the number of false-positive CNVs that need to be followed up with laboratory testing, we evaluated the relative performance of CNVPartition, PennCNV and QuantiSNP, and developed a statistical method for estimating sensitivity and positive predictive values of CNV calls and tested it on 96 duplicate samples in our dataset.
We found that the positive predictive rate increases with the number of probes in the CNV and the size of the CNV, with the highest positive predicted rates in CNVs of at least 500 kb and at least 100 probes. Our analysis also indicates that identifying CNVs reported by multiple programs can greatly improve the reproducibility rate and the positive predicted rate.
Our methods can be used by investigators to identify CNVs in genome-wide data with greater reliability.
Accuracy; Copy number variations; False positives; Genome-wide association studies
Event-related brain oscillations (EROs) represent highly heritable neuroelectrical correlates of human perception and cognitive performance that exhibit marked deficits in patients with various psychiatric disorders. We report the results of the first genome-wide association study (GWAS) of an ERO endophenotype – frontal theta ERO evoked by visual oddball targets during P300 response in 1,064 unrelated individuals drawn from a study of alcohol dependence. Forty-two SNPs of the Illumina HumanHap 1M microarray were selected from the theta ERO GWAS for replication in family-based samples (N = 1,095), with four markers revealing nominally significant association. The most significant marker from the two-stage study is rs4907240 located within ARID protein 5A gene (ARID5A) on chromosome 2q11 (unadjusted, Fisher’s combined P = 3.68 × 10−6). However, the most intriguing association to emerge is with rs7916403 in serotonin receptor gene HTR7 on chromosome 10q23 (combined P = 1.53 × 10−4), implicating the serotonergic system in the neurophysiological underpinnings of theta EROs. Moreover, promising SNPs were tested for association with diagnoses of alcohol dependence (DSM-IV), revealing a significant relationship with the HTR7 polymorphism among GWAS case-controls (P = 0.008). Significant recessive genetic effects were also detected for alcohol dependence in both case-control and family-based samples (P = 0.031 and 0.042, respectively), with the HTR7 risk allele corresponding to theta ERO reductions among homozygotes. These results suggest a role of the serotonergic system in the biological basis of alcohol dependence and underscore the utility of analyzing brain oscillations as a powerful approach to understanding complex genetic psychiatric disorders.
serotonin receptor gene (HTR7); serotonin receptor (5-HT7); event-related oscillation (ERO); alcohol dependence; genome-wide association study (GWAS)
The high-density-lipoprotein-(HDL-) associated esterase paraoxonase 1 (PON1) is a likely contributor to the antioxidant and antiatherosclerotic capabilities of HDL. Two nonsynonymous mutations in the structural gene, PON1, have been associated with variation in activity levels, but substantial interindividual differences remain unexplained and are greatest for substrates other than the eponymous paraoxon. PON1 activity levels were measured for three substrates—organophosphate paraoxon, arylester phenyl acetate, and lactone dihydrocoumarin—in 767 Mexican American individuals from San Antonio, Texas. Genetic influences on activity levels for each substrate were evaluated by association with approximately one million single nucleotide polymorphism (SNPs) while conditioning on PON1 genotypes. Significant associations were detected at five loci including regions on chromosomes 4 and 17 known to be associated with atherosclerosis and lipoprotein regulation and loci on chromosome 3 that regulate ubiquitous transcription factors. These loci explain 7.8% of variation in PON1 activity with lactone as a substrate, 5.6% with the arylester, and 3.0% with paraoxon. In light of the potential importance of PON1 in preventing cardiovascular disease/events, these novel loci merit further investigation.
Elevated arterial pulse pressure (PP) and blood pressure (BP) can lead to atrophy of cerebral white matter (WM), potentially due to shared genetic factors. We calculated the magnitude of shared genetic variance between BP and fractional anisotropy (FA) of water diffusion, a sensitive measurement of WM integrity in a well-characterized population of Mexican-Americans. The patterns of whole-brain and regional genetic overlap between BP and FA were interpreted in the context the pulse-wave encephalopathy (PWE) theory. We also tested whether regional pattern in genetic pleiotropy is modulated by the phylogeny of WM development. BP and high-resolution (1.7×1.7×3mm, 55 directions) diffusion tensor imaging (DTI) data were analyzed for 332 (202 females; mean age=47.9±13.3years) members of the San Antonio Family Heart Study. Bivariate genetic correlation analysis was used to calculate the genetic overlap between several BP measurements [PP, systolic (SBP) and diastolic (DBP)] and FA (whole-brain and regional values). Intersubject variance in PP and SBP exhibited a significant genetic overlap with variance in whole-brain FA values, sharing 36% and 22% of genetic variance, respectively. Regionally, shared genetic variance was significantly influenced by rates of WM development (r=−.75, p=0.01). The pattern of genetic overlap between BP and WM integrity was generally in-agreement with the PWE theory. Our study provides evidence that a set of pleiotropically acting genetic factors jointly influence phenotypic variation in BP and WM integrity. The magnitude of this overlap appears to be influenced by phylogeny of WM development suggesting a possible role for genotype-by-age interactions.
Population science; genetics; blood pressure; pulse pressure; white matter integrity; fractional anisotropy; diffusion tensor imaging; DTI
To identify genetic variation influencing serum bilirubin levels in American Indians, we performed genome-wide screening and association analyses in the Strong Heart Family Study. Bilirubin is an endogenous antioxidant that has demonstrated an inverse relationship with cardiovascular disease. Genetic variation within the promoter region of uridine diphosphate glucuronosyltransferase (UGT1A1) on chromosome 2q has been associated with elevated serum bilirubin levels in European populations. However, no study has investigated the UGT1A1 promoter in American Indians.
Statistical analyses were carried out with 3,484 participants aged 14 to 93 years recruited from three geographic areas in the United States; Arizona, Oklahoma, and North and South Dakota.
Variance components linkage analysis detected a quantitative trait locus (QTL) for bilirubin on chromosome 2q in the combined centers (LOD = 6.61, P = 4.24 × 10−6) and in Oklahoma (LOD = 5.65, P = 4.57 24 × 10−5). Genetic association of the UGT1A1 promoter polymorphism was significant for all geographic locations. After adjustment using conditional linkage for UGT1A1 promoter variance, the linkage signal dropped to 1.10 in the combined sample and to 3.32 (P = 0.02) in Oklahoma, indicating this polymorphism is not completely responsible for the linkage signal in American Indians. We also detected suggestive linkage signals in the Dakotas on chromosome 10p12 (LOD = 2.18) and in the combined centers (LOD = 2.24) on chromosome 10q21.
Replication of a serum bilirubin QTL on chromosome 2q in American Indians implicates UGT1A1 but further genotyping is warranted to identify additional causative polymorphisms. Evidence also supports a potential novel locus for bilirubin on chromosome 10. Am. J. Hum. Biol. 23:118–125, 2011.
Endophenotypes reflect more proximal effects of genes than diagnostic categories, hence providing a more powerful strategy in searching for genes involved in complex psychiatric disorders. There is strong evidence suggesting the P3 amplitude of the event-related potential (ERP) as an endophenotype for the risk of alcoholism and other disinhibitory disorders. Recent studies demonstrated a crucial role of corticotropin releasing hormone receptor 1 (CRHR1) in the environmental stress response and ethanol self-administration in animal models. The aim of the present study was to test the potential associations between single-nucleotide polymorphisms (SNPs) in the CRHR1 gene and the quantitative trait, P3 amplitude during the processing of visual target signals in an oddball paradigm, as well as alcohol dependence diagnosis.
We analyzed a sample from the Collaborative Study on the Genetics of Alcoholism (COGA) comprising 1049 Caucasian subjects from 209 families (including 472 alcohol-dependent individuals). Quantitative transmission disequilibrium test (QTDT) and family-based association test (FBAT) were used to test the association, and false discovery rate (FDR) was applied to correct for multiple comparisons.
Significant associations (p < 0.05) were found between the P3 amplitude and alcohol dependence with multiple SNPs in the CRHR1 gene.
Our results suggest that CRHR1 may be involved in modulating the P3 component of the ERP during information processing and in vulnerability to alcoholism. These findings underscore the utility of electrophysiology and the endophenotype approach in the genetic study of psychiatric disorders.
P3; Disinhibition; Endophenotype; Stress; Corticotropin Releasing Factor (CRF)
The Protein C anticoagulant pathway regulates blood coagulation by preventing the inadequate formation of thrombi. It has two main plasma components: protein C and protein S. Individuals with protein C or protein S deficiency present a dramatically increased incidence of thromboembolic disorders. Here, we present the results of a genome-wide association study (GWAS) for protein C and protein S plasma levels in a set of extended pedigrees from the Genetic Analysis of Idiopathic Thrombophilia (GAIT) Project. A total number of 397 individuals from 21 families were typed for 307,984 SNPs using the Infinium® 317 k Beadchip (Illumina). Protein C and protein S (free, functional and total) plasma levels were determined with biochemical assays for all participants. Association with phenotypes was investigated through variance component analysis. After correcting for multiple testing, two SNPs for protein C plasma levels (rs867186 and rs8119351) and another two for free protein S plasma levels (rs1413885 and rs1570868) remained significant on a genome-wide level, located in and around the PROCR and the DNAJC6 genomic regions respectively. No SNPs were significantly associated with functional or total protein S plasma levels, although rs1413885 from DNAJC6 showed suggestive association with the functional protein S phenotype, possibly indicating that this locus plays an important role in protein S metabolism. Our results provide evidence that PROCR and DNAJC6 might play a role in protein C and free protein S plasma levels in the population studied, warranting further investigation on the role of these loci in the etiology of venous thromboembolism and other thrombotic diseases.
Genetic Analysis Workshop 17 (GAW17) provided a platform for evaluating existing statistical genetic methods and for developing novel methods to analyze rare variants that modulate complex traits. In this article, we present an overview of the 1000 Genomes Project exome data and simulated phenotype data that were distributed to GAW17 participants for analyses, the different issues addressed by the participants, and the process of preparation of manuscripts resulting from the discussions during the workshop.
The data set simulated for Genetic Analysis Workshop 17 was designed to mimic a subset of data that might be produced in a full exome screen for a complex disorder and related risk factors in order to permit workshop participants to investigate issues of study design and statistical genetic analysis. Real sequence data from the 1000 Genomes Project formed the basis for simulating a common disease trait with a prevalence of 30% and three related quantitative risk factors in a sample of 697 unrelated individuals and a second sample of 697 individuals in large, extended pedigrees. Called genotypes for 24,487 autosomal markers assigned to 3,205 genes and simulated affection status, quantitative traits, age, sex, pedigree relationships, and cigarette smoking were provided to workshop participants. The simulating model included both common and rare variants with minor allele frequencies ranging from 0.07% to 25.8% and a wide range of effect sizes for these variants. Genotype-smoking interaction effects were included for variants in one gene. Functional variants were concentrated in genes selected from specific biological pathways and were selected on the basis of the predicted deleteriousness of the coding change. For each sample, unrelated individuals and family, 200 replicates of the phenotypes were simulated.
Joint analyses of correlated phenotypes in genetic epidemiology studies are common. However, these analyses primarily focus on genetic correlation between traits and do not take into account environmental correlation. We describe a method that optimizes the genetic signal by accounting for stochastic environmental noise through joint analysis of a discrete trait and a correlated quantitative marker. We conducted bivariate analyses where heritability and the environmental correlation between the discrete and quantitative traits were calculated using Genetic Analysis Workshop 17 (GAW17) family data. The resulting inverse value of the environmental correlation between these traits was then used to determine a new β coefficient for each quantitative trait and was constrained in a univariate model. We conducted genetic association tests on 7,087 nonsynonymous SNPs in three GAW17 family replicates for Affected status with the β coefficient fixed for three quantitative phenotypes and compared these to an association model where the β coefficient was allowed to vary. Bivariate environmental correlations were 0.64 (± 0.09) for Q1, 0.798 (± 0.076) for Q2, and −0.169 (± 0.18) for Q4. Heritability of Affected status improved in each univariate model where a constrained β coefficient was used to account for stochastic environmental effects. No genome-wide significant associations were identified for either method but we demonstrated that constraining β for covariates slightly improved the genetic signal for Affected status. This environmental regression approach allows for increased heritability when the β coefficient for a highly correlated quantitative covariate is constrained and increases the genetic signal for the discrete trait.
The synthetic association hypothesis proposes that common genetic variants detectable in genome-wide association studies may reflect the net phenotypic effect of multiple rare polymorphisms distributed broadly within the focal gene rather than, as often assumed, the effect of common functional variants in high linkage disequilibrium with the focal marker. In a recent study, Dickson and colleagues demonstrated synthetic association in simulations and in two well-characterized, highly polymorphic human disease genes. The converse of this hypothesis is that rare variant genotypes must be correlated with common variant genotypes often enough to make the phenomenon of synthetic association possible. Here we used the exome genotype data provided for Genetic Analysis Workshop 17 to ask how often, how well, and under what conditions rare variant genotypes predict the genotypes of common variants within the same gene. We found nominal evidence of correlation between rare and common variants in 21-30% of cases examined for unrelated individuals; this rate increased to 38-44% for related individuals, underscoring the segregation that underlies synthetic association.
Choosing the appropriate neuroimaging phenotype is critical to successfully identify genes that influence brain structure or function. While neuroimaging methods provide numerous potential phenotypes, their role for imaging genetics studies are unclear. Here we examine the relationship between brain volume, grey matter volume, cortical thickness and surface area, from a genetic standpoint. Four hundred and eighty-six individuals from randomly ascertained extended pedigrees with high-quality T1-weighted neuroanatomic MRI images participated in the study. Surface-based and voxel-based representations of brain structure were derived, using automated methods, and these measurements were analysed using a variance-components method to identify the heritability of these traits and their genetic correlations. All neuroanatomic traits were significantly influenced by genetic factors. Cortical thickness and surface area measurements were found to be genetically and phenotypically independent. While both thickness and area influenced volume measurements of cortical grey matter, volume was more closely related to surface area than cortical thickness. This trend was observed for both the volume-based and surface-based techniques. The results suggest that surface area and cortical thickness measurements should be considered separately and preferred over gray matter volumes for imaging genetic studies.
brain cortical thickness; brain surface area; heritability
Heart rate (HR) has been identified as a risk factor for cardiovascular disease (CVD), yet little is known regarding genetic factors influencing this phenotype. Previous research in American Indians (AIs) from the Strong Heart Family Study (SHFS) identified a significant quantitative trait locus (QTL) for HR on chromosome 9p21. Genetic association on HR was conducted in the SHFS. HR was measured from electrocardiogram (ECG) and echocardiograph (Echo) Doppler recordings. We examined 2248 single-nucleotide polymorphisms (SNPs) on chromosome 9p21 for association using a gene-centric statistical test. We replicated the aforementioned QTL [logarithm of odds (LOD) = 4.83; genome-wide P= 0.0003] on chromosome 9p21 in one SHFS population using joint linkage of ECG and Echo HR. After correcting for effective number of SNPs using a gene-centric test, six SNPs (rs7875153, rs7848524, rs4446809, rs10964759, rs1125488 and rs7853123) remained significant. We applied a novel bivariate association method, which was a joint test of association of a single locus to two traits using a standard additive genetic model. The SNP, rs7875153, provided the strongest evidence for association (P = 7.14 × 10−6). This SNP (rs7875153) is rare (minor allele frequency = 0.02) in AIs and is located within intron 9 of the gene KIAA1797. To support this association, we applied lymphocyte RNA expression data from the San Antonio Family Heart Study, a longitudinal study of CVD in Mexican Americans. Expression levels of KIAA1797 were significantly associated (P = 0.012) with HR. These findings in independent populations support that KIAA1797 genetic variation may be associated with HR but elucidation of a functional relationship requires additional study.
Sensation seeking is a heritable personality trait that has been reliably linked to behavior disorders. The dopamine system has been hypothesized to contribute to individual differences in sensation seeking, and both experimental and observational studies in humans and non-human animals provide evidence for this relationship. We present here a candidate-system approach to genetic association analysis of sensation seeking, in which single nucleotide polymorphisms (SNPs) from a number of dopaminergic genes were analyzed. Using 273 SNPs from eight dopamine genes in a sample of 635 unrelated individuals, we examined the aggregate effects of those SNPs significantly associated with sensation seeking. Multiple SNPs in four dopamine genes accounted for significant variance in sensation seeking. These results suggest that aggregation of multiple SNPs within genes relevant to a specific neurobiological system into a “genetic risk score” may explain a nontrivial proportion of variance in human traits.
sensation seeking; dopamine; candidate gene; association study
Polymorphisms of the gene encoding the regulator of G protein signaling, subtype 4 (RGS4), may be associated with schizophrenia. Among first-episode schizophrenia patients, they are also associated with dorsolateral prefrontal cortex (DLPFC) volume. The DLPFC is a key region that regulates heritable cognitive functions implicated in schizophrenia pathogenesis. To further understand the relationship of RGS4 variants to schizophrenia, we examined their associations with cognitive functions among schizophrenia patients and their relatives. We analyzed 31 multiplex, multigenerational Caucasian families with schizophrenia recruited on the basis of 2 affected first-degree relatives. All participants underwent a computerized neurocognitive battery that evaluates accuracy and speed (response time) of performance on abstraction/mental flexibility; attention; verbal, spatial, and face memory; and spatial ability. “Tag” single-nucleotide polymorphisms (SNPs) representing common polymorphisms were genotyped. Measured genotype analyses accounting for family relationships were performed using Sequential Oligogenic Linkage Analysis Routines. SNPs rs10917670 (“SNP1”) and rs951439 (“SNP7”) were associated with face memory speed (P = .0003) at a significance level that survived Bonferroni correction (P = .039). The same SNPs have earlier been reported to be associated with schizophrenia. There also were uncorrected associations with rs10917670 (“SNP1”) and rs951439 (“SNP7”) on face memory efficiency (P = .03) and verbal memory efficiency (P = 0.02), rs28757217 on abstraction/mental flexibility speed (P = .02) and verbal memory efficiency (P = .03), SNP18 (rs2661319) on spatial memory accuracy (P = 0.02) and face memory speed (P = .03). RGS4 polymorphisms are associated with variations in cognitive functions and contribute a small but statistically significant proportion of variance in a family-based sample.
schizophrenia; genetics; cognition; memory
Alcohol dependence is a complex disease, and although linkage and candidate gene studies have identified several genes associated with the risk for alcoholism, these explain only a portion of the risk.
We carried out a genome-wide association study (GWAS) on a case-control sample drawn from the families in the Collaborative Study on the Genetics of Alcoholism. The cases all met diagnostic criteria for alcohol dependence according to the Diagnostic and Statistical Manual of the American Psychiatric Association Fourth Edition (DSM-IV); controls all consumed alcohol but were not dependent on alcohol or illicit drugs. To prioritize among the strongest candidates, we genotyped most of the top 199 SNPs (p ≤ 2.1 × 10−4) in a sample of alcohol dependent families and performed pedigree-based association analysis. We also examined whether the genes harboring the top SNPs were expressed in human brain or were differentially expressed in the presence of ethanol in lymphoblastoid cells.
Although no single SNP met genome-wide criteria for significance, there were several clusters of SNPs that provided mutual support. Combining evidence from the case-control study, the followup in families, and gene expression provided strongest support for the association of a cluster of genes on chromosome 11 (SLC22A18, PHLDA2, NAP1L4, SNORA54, CARS, and OSBPL5) with alcohol dependence. Several SNPs nominated as candidates in earlier GWAS studies replicated in ours, including CPE, DNASE2B, SLC10A2,ARL6IP5, ID4, GATA4, SYNE1 and ADCY3.
We have identified several promising associations that warrant further examination in independent samples.
alcohol dependence; genome-wide association study; case-control study; family study; gene expression
Chronic kidney disease (CKD) is an important public health problem in American Indian populations. Recent research has identified associations of polymorphisms in the myosin heavy chain type II isoform A (MYH9) gene with hypertensive CKD in African-Americans. Whether these associations are also present among American Indian individuals is unknown. To evaluate the role of genetic polymorphisms in the MYH9 gene on kidney disease in American Indians, we genotyped 25 SNPs in the MYH9 gene region in 1,119 comparatively unrelated individuals. Four SNPs failed, and one SNP was monomorphic. We inferred haplotypes using seven SNPs within the region of the previously described E haplotype using Phase v2.1. We studied the association between 20 MYH9 SNPs with kidney function (estimated glomerular filtration rate, eGFR) and CKD (eGFR < 60 ml/min/1.73 m2 or renal replacement therapy or kidney transplant) using age-, sex- and center-adjusted models and measured genotyped within the variance component models. MYH9 SNPs were not significantly associated with kidney traits in additive or recessive genetic adjusted models. MYH9 haplotypes were also not significantly associated with kidney outcomes. In conclusion, common variants in MYH9 polymorphisms may not confer an increased risk of CKD in American Indian populations. Identification of the actual functional genetic variation responsible for the associations seen in African-Americans will likely help to clarify the lack of replication of this gene in our population of American Indians.